diff --git a/build.gradle.kts b/build.gradle.kts
index 4ca1b5f..85f40f3 100644
--- a/build.gradle.kts
+++ b/build.gradle.kts
@@ -5,7 +5,7 @@ plugins {
 
 qupathExtension {
 	name = "qupath-extension-djl"
-	version = "0.4.1"
+	version = "0.4.2"
 	group = "io.github.qupath"
 	description = "QuPath extension to use Deep Java Library"
 	automaticModule = "qupath.extension.djl"
diff --git a/src/main/java/qupath/ext/djl/DjlTools.java b/src/main/java/qupath/ext/djl/DjlTools.java
index 9998c5f..f5670b9 100644
--- a/src/main/java/qupath/ext/djl/DjlTools.java
+++ b/src/main/java/qupath/ext/djl/DjlTools.java
@@ -404,7 +404,9 @@ public static NDArray matToNDArray(NDManager manager, Mat mat, String ndLayout)
 			array = manager.create(buffer, shape, dataType);			
 		} else if (("NCHW".equals(ndLayout) || "CHW".equals(ndLayout)) && (nChannels == 3L || nChannels == 4L)) {
 			// Channels-first - an OpenCV blob is defined to have the order NCHW, but an Image can only have 1, 3 or 4 channels
-			array = manager.create(opencv_dnn.blobFromImage(mat).createBuffer(), shape, dataType);
+			try (var blob = opencv_dnn.blobFromImage(mat)) {
+				array = manager.create(blob.createBuffer(), shape, dataType);
+			}
 		} else {
 			// Really awkward strategy to handle channels in an uncommon place (shouldn't actually occur?)
 			var shapeDims = shape.getShape().clone();